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Fourier-Information Duality in the Identity Management Problem

  • Xiaoye Jiang
  • Jonathan Huang
  • Leonidas Guibas
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6912)

Abstract

We compare two recently proposed approaches for representing probability distributions over the space of permutations in the context of multi-target tracking. We show that these two representations, the Fourier approximation and the information form approximation can both be viewed as low dimensional projections of a true distribution, but with respect to different metrics. We identify the strengths and weaknesses of each approximation, and propose an algorithm for converting between the two forms, allowing for a hybrid approach that draws on the strengths of both representations. We show experimental evidence that there are situations where hybrid algorithms are favorable.

Keywords

Identity Management Tracking Accuracy Information Form Simulated Crowd Loopy Belief Propagation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Xiaoye Jiang
    • 1
  • Jonathan Huang
    • 2
  • Leonidas Guibas
    • 1
  1. 1.Stanford UniversityStanfordUSA
  2. 2.Carnegie Mellon UniversityPittsburghUSA

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